Ankle-brachial index in relation to the natriuretic peptide system polymorphisms and urinary sodium excretion in Chinese

The association of arterial stiffness with estimated excretion levels of urinary sodium and potassium and their ratio in Chinese adults

Arterial stiffness is an independent cardiovascular risk factor. However, the association between sodium/potassium intake and arterial stiffness in the Chinese population is unclear. Therefore, we performed a large, community-based cross-sectional study to reach a more definitive conclusion. The study was conducted at the Third Xiangya Hospital in Changsha between August 2017 and September 2019. Urinary sodium, potassium, and creatinine levels were tested from spot urine samples during physical examinations of each recruited participant. The 24-hour estimated urinary sodium excretion (eUNaE) and estimated urinary potassium excretion (eUKE) levels were calculated using the Kawasaki formula (used as a surrogate for intake). The brachial-ankle pulse wave velocity (baPWV) and ankle brachial index (ABI) were measured using an automatic waveform analyzer. In 22,557 subjects with an average age of 49.3 ± 10.3 years, the relationships of the ABI and baPWV with the levels of eUNaE, eUKE and the ratio of sodium to potassium (Na/K ratio) were analyzed. A significant negative relationship was found between the eUKE and baPWV levels (β = 2.41, p < 0.01), whereas the Na/K ratio was positively associated with baPWV (β = 2.46, p < 0.01), especially in the overweight and hypertensive populations (both pinteraction = 0.04). The association of eUNaE quartiles with baPWV presented a J-shaped curve after adjusting for confounders. In addition, a positive association was observed between the Na/K ratio and the ABI (β = 0.002, p < 0.01). In this study, high potassium and/or low sodium intake was further confirmed to be related to vascular stiffness in Chinese individuals.

Searching for the Genetic Determinants of Peripheral Arterial Disease: A Review of the Literature and Future Directions

Peripheral arterial disease (PAD) is a significant but under-recognized disease that is poorly understood despite population-scale genetic studies. To address this morbid disease, clinicians need additional tools to identify, prevent, and treat patients at risk for PAD. Genetic studies of coronary artery disease have yielded promising results for clinical application, which have thus far been lacking in PAD. In this article, we review recent findings, discuss limitations, and propose future directions of genomic study and clinical application. However, despite many studies, we still lack definitive genetic markers for PAD. This can be attributed to the heterogeneity of PAD's pathogenesis and clinical manifestations, as well as inconsistencies in study methodologies, limitations of current genetic assessment techniques, incompletely comprehended molecular pathophysiology, and confounding generalized atherosclerotic risk factors. The goals of this review are to evaluate the limitations of our current genetic knowledge of PAD and to propose approaches to expedite the identification of valuable markers of PAD.

Inflammatory Mediators Across the Spectrum of Ankle-Brachial Index

Aim: Peripheral artery disease (PAD) is a manifestation of atherosclerosis with poor prognosis. It is generally complicated by vascular calcification, which is located either in the intima as patchy infiltrates; or circumferentially in the media, also known as medial arterial calcification (MAC). Obstructive PAD is reflected by low anklebrachial index (ABI ≤ 0.9), whereas MAC is revealed by high ABI (ABI > 1.4). Considering the increase in cardiovascular mortality at both ends of the ABI spectrum, this study aimed to explore the underlying pathology through cytokines with established prognostic significance; namely pentraxin-3(PTX3), high sensitivity C-reactive protein (hsCRP), copeptin, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), NT-proBNP, and neopterin.

Methods: We categorized 180 patients with previous multivessel coronary artery bypass grafting surgery into three groups based on their ABI measurements; 60 patients with ABI ≤ 0.9, 60 patients with ABI within 0.91 and 1.4 (normal ABI), and 60 patients with ABI > 1.4 constituted the “PAD,” “normal,” “MAC” groups, respectively. The circulating levels of the biochemical markers were determined.

Results: In the PAD group, the cytokine levels with predominantly proatherogenic actions such as PTX3, hsCRP, copeptin, and sTREM-1 were increased and these cytokine levels declined as the ABI increased. In the MAC group, the cytokine concentrations with pleiotropic actions such as NT-proBNP and neopterin increased and; NT-proBNP and neopterin concentrations decreased as ABI decreased. The linear regression analysis revealed that neopterin (β = 0.72), PTX3 (β = −0.32), and copeptin (β = −0.48) were independent predictors of ABI.

Conclusions: These findings suggest that different inflammatory pathways influence the pathology at the opposing ends of the ABI spectrum. Consequently, we suggest that PTX3, copeptin, and neopterin are promising biomarkers for future research.

Computational drug repositioning for peripheral arterial disease: prediction of anti-inflammatory and pro-angiogenic therapeutics

Peripheral arterial disease (PAD) results from atherosclerosis that leads to blocked arteries and reduced blood flow, most commonly in the arteries of the legs. PAD clinical trials to induce angiogenesis to improve blood flow conducted in the last decade have not succeeded. We have recently constructed PADPIN, protein-protein interaction network (PIN) of PAD, and here we combine it with the drug-target relations to identify potential drug targets for PAD. Specifically, the proteins in the PADPIN were classified as belonging to the angiome, immunome, and arteriome, characterizing the processes of angiogenesis, immune response/inflammation, and arteriogenesis, respectively. Using the network-based approach we predict the candidate drugs for repositioning that have potential applications to PAD. By compiling the drug information in two drug databases DrugBank and PharmGKB, we predict FDA-approved drugs whose targets are the proteins annotated as anti-angiogenic and pro-inflammatory, respectively. Examples of pro-angiogenic drugs are carvedilol and urokinase. Examples of anti-inflammatory drugs are ACE inhibitors and maraviroc. This is the first computational drug repositioning study for PAD.